Previous Conferences & Workshops

Oct
09
2012

Computer Science/Discrete Mathematics Seminar II

On the Conjectures of Nonnegative $k$-Sum and Hypergraph Matching
10:30am|S-101

A twenty-year old conjecture by Manickam, Mikl\'os, and Singhi asked whether for any integers $n, k$ satisfying $n \ge 4k$, every set of $n$ real numbers with nonnegative sum always has at least $\binom{n-1}{k-1}$ $k$-element subsets whose sum is...

Oct
08
2012

Members’ Seminar

Parallel Repetition of Two Prover Games: A Survey
2:00pm|S-101

I will give an introduction to the problem of parallel repetition of two-prover games and its applications and related results in theoretical computer science (the PCP theorem, hardness of approximation), mathematics (the geometry of foams, tiling...

Oct
08
2012

Computer Science/Discrete Mathematics Seminar I

Identity Testing of Tensors, Low Rank Recovery and Compressed Sensing
Amir Shpilka
11:15am|S-101

A matrix A naturally defines a quadratic form x^tAy. If A is of rank <=r, then the rank<=r decomposition of A corresponds naturally to a size ~2nr circuit for computing the quadratic form. It is clear how to perform "white box" polynomial identity testing for such circuits, and the motivating question for this work is to explore black-box identity testing. The probabilistic method shows that there is a size ~2nr hitting set for such polynomials. In this work we match this bound (over large fields), which is optimal up to constant factors. Further, we explore how A can be reconstructed from the evaluations of the quadratic form. Similar probabilistic constructions show that there exist ~4nr evaluations which determine any such matrix A. Again, we match this bound (over large fields) with an explicit construction, and furthermore give a polynomial-time algorithm to reconstruct A from such evaluations. More generally, we show an efficient reduction from (exact) low-rank matrix reconstruction to (exact) sparse recovery. This reduction is novel in the compressed-sensing realm as it is field independent and unrelated to convex optimization. Finally, using matrices as a base case we also derive a quasi-polynomial hitting set for higher-order tensors. Joint work with Michael Forbes.

Oct
05
2012

Joint IAS/Princeton University Symplectic Geometry Seminar

Symplectic Geometry and Quantum Noise
Leonid Polterovich
4:30pm|S-101

We discuss a quantum counterpart, in the sense of the Berezin-Toeplitz quantization, of certain constraints on Poisson brackets coming from "hard" symplectic geometry. It turns out that they can be interpreted in terms of the quantum noise of...

Oct
04
2012

Joint IAS/Princeton University Number Theory Seminar

A Converse Theorem for SL_2
Vinayak Vatsal
4:30pm|Fine Hall 214

We'll prove a converse theorem for forms forms on SL_2. While the theorem is easy to prove once it has been formulated, the number-theoretic considerations leading to its formulation nevertheless pose some interesting and apparently unsolved...